This course will show practical applications and implementations of the contents of the “Deep Learning and Neural Nets I (3 VL)” class. Students will exercise the theory presented in the accompanying lecture and solve programming assignments. Programming assignments will be done in Python using the PyTorch framework.
Subject
This course teaches how to implement
a deep learning framework with automatic differentiation
fully-connected and convolutional layers
optimisation algorithms and components for accelerating learning in Python and how to build full networks to solve practical tasks.
Criteria for evaluation
bi-weekly assignments, exam at the end of the semester
Methods
Slide presentations, presentations on blackboard, discussions, and code examples
